• CELLMED
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• v.11 no.1
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• pp.1.1-1.4
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• 2021

Background: Amavata is a disease that occurs as a result of the error of metabolism. Poor dietary habits and faulty Dincharya (daily regimen) and ritucharya (seasonal regimen) leading to deranged metabolism and Agni (metabolic fire) which results in the formation of Ama(undigested product of metabolism). When Amaconceals with Vata(subtle energy associated with movement) and circulates in the body under the influence of Vyana Vayu (omnipresent air)it clogs the srotasas (microchannels) and initiates the inflammatory cascade. Amavata is commonly correlated with rheumatoid arthritis (RA) while other forms of auto-immune disorders can also be included in Amavata.Dysbiosis of the gut microbiota (GM) has been connected to the onset of diverse autoimmune diseases. In this study, it was hypothesized that Panchakarma (bio-purificatory methods) based intervention such as Virechana Karma (therapeutic purgation) may influence microbiota. Materials and Methods: Various Ayurvedic literature were reviewed for the etiopathogenesis of Amavata. Different databases were searched with research papers related to Gut Dysbiosis and autoimmunity and management of RA. A connecting link between Intestinal Dysbiosis with the autoimmune mechanisms was established and it was also found that the bowel cleansing introduced a change to the GM. Conclusion: It was concluded that Virechana karma is effective in gut flora Dysbiosis. This study aims to correlate the ancient Ayurvedic principles related to Agni Bala(metabolic energy) and biopurificatory treatment modalities like Virechana karma (therapeutic purgation)with the modern concept of gut microbiota and its role in the pathogenesis of various autoimmune disorders such as rheumatoid arthritis. The article creates an understanding about principles of Ayurveda and its rationality in today's scientific world and thereby opens newer vistas of research in therapeutics from Ayurveda, which may be helpful in the management of various immune-mediated Diseases through Ayurveda.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.9
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• pp.441-450
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• 2002

In this paper, optimal tuning problem of power system stabilizer using IA-QFT is investigated to improve power system dynamic stability in spite of parameter variation and disturbance uncertainties. The most important feature of QFT is that it is able to deal with the design problem of complicated uncertain plants. However, loop shaping is currently performed in computer aided design environments manually and it is usually a trial and error procedure. It is difficult to design a controller to satisfy all specifications manually. To solve this problem, a study of design automation using IA needs to be taken into account. The robustness of the proposed controller has been investigated on a single machine infinite bus model. The results are shown that the proposed PSS using IA-QFT is more robust than conventional PSS.

• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.178-186
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• 2011

Line tracking is a well defined method of mobile robot navigation. It is simple in concept, technically easy to implement, and already employed in many industrial sites. Among several different line tracking methods, magnetic sensing is widely used in practice. In comparison, vision-based tracking is less popular due mainly to its sensitivity to surrounding conditions such as brightness and floor characteristics although vision is the most powerful robotic sensing capability. In this paper, a vision-based robust path line detection technique is proposed for the navigation of a mobile robot assuming uncontrollable surrounding conditions. The technique proposed has four processing steps; color space transformation, pixel-level line sensing, block-level line sensing, and robot navigation control. This technique effectively uses hue and saturation color values in the line sensing so to be insensitive to the brightness variation. Line finding in block-level makes not only the technique immune from the error of line pixel detection but also the robot control easy. The proposed technique was tested with a real mobile robot and proved its effectiveness.

• Journal of Communications and Networks
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• v.13 no.5
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• pp.442-448
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• 2011

It's a challenging task to design a high performance modulation for satellite and space communications due to the limited power and bandwidth resource. Constant envelope modulation is an attractive scheme to be used in such cases for their needlessness of input power back-off about 2~3 dB for avoidance of nonlinear distortion induced by high power amplifier. The envelope of Feher quadrature phase shift keying (FQPSK) has a least fluctuation of 0.18 dB (quasi constant envelope) and can be further improved. This paper improves FQPSK by defining a set of new waveform functions, which changes FQPSK to be a strictly constant envelope modulation. The performance of the FQPSK adopting new waveform is justified by analysis and simulation. The study results show that the novel FQPSK is immune to the impact of HPA and outperforms conventional FQPSK on bit error rate (BER) performance. The BER performance of this novel modulation is better than that of FQPSK by more than 0.5 dB at least and 2 dB at most.

• Journal of Power Electronics
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• v.15 no.4
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• pp.974-986
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• 2015

A novel inverter fault-tolerant control scheme is proposed to drive brushless DC motor. A fault-tolerant inverter and its three fault-tolerant schemes (i.e., phase A fault-tolerant, phase B fault-tolerant, and phase C fault-tolerant) are analyzed. Eight voltage vectors are summarized and a voltage vector selection table is used in the control scheme to improve the midpoint current of the split capacitors. A stator flux observer is proposed. The observer can improve flux estimation, which does not require any speed adaptation mechanism and is immune to speed estimation error. Global stability of the flux observer is guaranteed by the Lyapunov stability analysis. A novel stator resistance estimator is incorporated into the sensorless drive to compensate for the effects of stator resistance variation. DC offset effects are mitigated by introducing an integral component in the observer gains. Finally, a control system based on the control scheme is established. Simulation and experiment results show that the method is correct and feasible.

• Genomics & Informatics
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• v.18 no.4
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• pp.45.1-45.5
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• 2020

With the ongoing rise of coronavirus disease 2019 (COVID-19) pandemic across the globe, interests in COVID-19 antibody testing, also known as a serology test has grown, as a way to measure how far the infection has spread in the population and to identify individuals who may be immune. Recently, many countries reported their population based antibody titer study results. South Korea recently reported their third antibody formation rate, where it divided the study between the general population and the young male youths in their early twenties. As previously stated, these simple point estimates may be misinterpreted without proper estimation of standard error and confidence intervals. In this article, we provide an updated 95% confidence intervals for COVID-19 antibody formation rate for the Korean population using asymptotic, exact and Bayesian statistical estimation methods. As before, we found that the Wald method gives the narrowest interval among all asymptotic methods whereas mid p-value gives the narrowest among all exact methods and Jeffrey's method gives the narrowest from Bayesian method. The most conservative 95% confidence interval estimation shows that as of 00:00 November 23, 2020, at least 69,524 people were infected but not confirmed. It also shows that more positive cases were found among the young male in their twenties (0.22%), three times that of the general public (0.051%). This thereby calls for the quarantine authorities' need to strengthen quarantine managements for the early twenties in order to find the hidden infected people in the population.

• Journal of Gastric Cancer
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• v.23 no.3
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• pp.410-427
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• 2023

Recent advances in artificial intelligence (AI) have provided novel tools for rapid and precise pathologic diagnosis. The introduction of digital pathology has enabled the acquisition of scanned slide images that are essential for the application of AI. The application of AI for improved pathologic diagnosis includes the error-free detection of potentially negligible lesions, such as a minute focus of metastatic tumor cells in lymph nodes, the accurate diagnosis of potentially controversial histologic findings, such as very well-differentiated carcinomas mimicking normal epithelial tissues, and the pathological subtyping of the cancers. Additionally, the utilization of AI algorithms enables the precise decision of the score of immunohistochemical markers for targeted therapies, such as human epidermal growth factor receptor 2 and programmed death-ligand 1. Studies have revealed that AI assistance can reduce the discordance of interpretation between pathologists and more accurately predict clinical outcomes. Several approaches have been employed to develop novel biomarkers from histologic images using AI. Moreover, AI-assisted analysis of the cancer microenvironment showed that the distribution of tumor-infiltrating lymphocytes was related to the response to the immune checkpoint inhibitor therapy, emphasizing its value as a biomarker. As numerous studies have demonstrated the significance of AI-assisted interpretation and biomarker development, the AI-based approach will advance diagnostic pathology.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.5
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• pp.677-684
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• 2008

Accurate estimation of dry matter intake (DMI) is a prerequisite to meet animal performance targets without penalizing animal health and the environment. The objective of the current study was to evaluate some of the existing models in order to predict DMI when lactating dairy cows were offered a total mixed ration containing a high level of concentrates and locally produced agricultural by-products. Six popular models were chosen for DMI prediction (Brown et al., 1977; Rayburn and Fox, 1993; Agriculture Forestry and Fisheries Research Council Secretariat, 1999; National Research Council (NRC), 2001; Cornell Net Carbohydrate and Protein System (CNCPS), Fox et al., 2003; Fuentes-Pila et al., 2003). Databases for DMI comparison were constructed from two different sources: i) 12 commercial farm investigations and ii) a controlled dairy cow experiment. The model evaluation was performed using two different methods: i) linear regression analysis and ii) mean square error prediction analysis. In the commercial farm investigation, DMI predicted by Fuentes-Pila et al. (2003) was the most accurate when compared with the actual mean DMI, whilst the CNCPS prediction showed larger mean bias (difference between mean predicted and mean observed values). Similar results were observed in the controlled dairy cow experiment where the mean bias by Fuentes-Pila et al. (2003) was the smallest of all six chosen models. The more accurate prediction by Fuentes-Pila et al. (2003) could be attributed to the inclusion of dietary factors, particularly fiber as these factors were not considered in some models (i.e. NRC, 2001; CNCPS (Fox et al., 2003)). Linear regression analysis had little meaningful biological significance when evaluating models for prediction of DMI in this study. Further research is required to improve the accuracy of the models, and may recommend more mechanistic approaches to investigate feedstuffs (common to the Asian region), animal genotype, environmental conditions and their interaction, as the majority of the models employed are based on empirical approaches.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.69-74
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• 2016

Purpose Using a regression formula of the trendline near the coefficient of determination (R2) "1" by substituting the dependent variable of the standard curve to calculate the values of the independent variable. To determine the suitability of a regression equation by comparing the difference between the independent variables of the standard curve and the predicted independent variables. Materials and Methods Perkin Elmer Gamma-Counter machine was used for Standard curve of regression methods. TSH. TG-Ag (Thyroglobulin Antigen), Insulin that used materials and method test to compare the result from the Excel trendline of the regression formula. Results Each of the value of coefficient of determination ($R^2$) and Trendline $R^2=1$, Polynomial Trendline for TSH, $R^2=1$, Polynomial Trendline for TG-Ag, $R^2=0.9994$, Polynomial Trendline for Insulin. Conclusion We confirmed that IRMA immune method is found to the nearest trends elected a standard curve using polynomial trendline. The independent variables to predict the trend by using a polynomial trendline formula containing the error was a limitation.

• The Journal of the Korea Contents Association
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• v.14 no.3
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• pp.52-58
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• 2014

Point of care testing (POCT) is could be easily and economically performed and was widely used. In particular, the test items using immune chromatographic method has been conveniently used. But when an error occurs, we should reaffirmed the test results, but we could not reaffirm because the test line is disappeared as the time pass, and the test results are different between laboratory workers. Therefore, we developed multi-strip reader which can store images for the test results and can interpretate the test results automatically. Then we evaluated newly developed multi-strip reader for urine pregnancy test, the test results of the multi-strip reader was 100% matched with the previously results. Our newly developed multi-strip reader was convenient and economic, and will be widely used in many laboratories.